DEAPack

DEAPack is a source-audited Python toolkit for data envelopment analysis, efficiency measurement, productivity analysis, and environmental performance. The redesigned 2.x API uses the lowercase deapack import and a common data, technology, result, visualization, and reporting architecture.

2.0.0 is the first stable release of the redesigned DEAPack 2.x line. Its 33 dataset fingerprints have exact item-level license and attribution mappings.

Installation

Install the stable release with:

python -m pip install "DEAPack==2.0.0"

Python 3.10, 3.11, 3.12, and 3.13 are supported. NumPy, pandas, and SciPy are the only required runtime dependencies; ordinary linear programmes use the HiGHS solver bundled through SciPy. Install DEAPack[viz] for the optional Matplotlib result views.

Quick start

import pandas as pd

from deapack import BCCInput, DEAData

frame = pd.DataFrame(
    {
        "dmu": ["A", "B", "C", "D"],
        "input": [1.0, 2.0, 3.0, 4.0],
        "output": [1.0, 3.0, 4.0, 4.0],
    }
)
data = DEAData.from_frame(
    frame,
    dmu="dmu",
    inputs="input",
    outputs="output",
)

result = BCCInput().fit(data)
print(result.summary())
print(result.peers("D"))

Results expose named summary, target, slack, peer, dual, component, and diagnostic tables only when the corresponding numerical and economic account has been certified. They can also produce a self-contained HTML brief and a deterministic audit archive.

Scope

The release covers the major classical radial and non-radial families, directional and generalized-distance analysis, price-informed economic efficiency, undesirable-output and environmental technologies, Malmquist and related productivity accounts, network and dynamic production, panel models, and radial metafrontiers. The installed discovery catalog is the authoritative list of public methods:

from deapack import list_methods

for method in list_methods():
    print(method.method_id)

Statistical inference, Färe--Primont productivity, generic congestion, automatic EBM calibration, and several source-incomplete variants remain explicit next-version work rather than provisional APIs.

Documentation and migration

• Package Documentation source
• English Handbook source
• Chinese Handbook catalogs
• 2.x migration guide
• Release notes
• Contribution guide
• Issue tracker

DEAPack 2.x is a greenfield API. Historical import DEAPack and ProdPack scripts require an explicit migration; the 2.x wheel intentionally provides only import deapack.

Citation and license

Use the repository's CITATION.cff and record the exact version and commit used. The DEAPack software component is licensed under GPL-3.0-only. Bundled dataset content is released only when its provenance record identifies confirmed licensing authority, an approved redistribution status, content license, attribution, and required notice; it does not inherit GPL merely by being represented in a Python file. All 33 current dataset fingerprints have exact mappings: 30 project-created or independently selected fixtures and one external dataset use CC-BY-4.0, while two external datasets retain upstream MIT notices. Package Documentation and Bilingual Handbook Preview 1 are separate components and are cited and licensed separately.